Effects of potassium fertilizer on rhizosphere microbial diversity and community assembly in sugarcane.
Bibliographic record
Abstract
, respectively. The abundant populations mainly concentrated in a few dominant species. Potassium application significantly affected species composition and community structures of the rhizosphere microorganisms. Under potassium application, soil urease, soil organic matter, and catalase were the key limiting factors, which could affect community structures of the abundant and rare microbial populations. The effects of potassium application on the rhizosphere bacterial community were greater than those on the fungal community, and the effects on the abundant microbial community was greater than that on the rare one. Community assembly of bacteria and fungi were predominantly driven by determini-stic processes in the sugarcane rhizosphere, with the heterogeneity selection dominating in bacteria and the homogeneity selection dominating in fungi. The deterministic processes played a key role in the abundant and rare communities assembly. In conclusion, our results demonstrated that potassium application significantly affected soil nutrients and enzyme activities. The potassium application could enhance the diversity of abundant and rare populations of bacteria and fungi and regulate soil microbial community assembly in the rhizosphere.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".